Abstract
Molecular dynamics (MD) is the only computational tool that, without any approximation, can be applied to study atomic level phenomena involving radiation produced point-defects and their evolution driven by mutual interaction. Kinetic Monte Carlo (KMC) is suitable to extend the timeframe of an atomic level simulation to simulate an irradiation process, but all mechanisms involved must be known in advance, e.g. from MD studies. The present work is an effort to integrate artificial intelligence (AI) techniques, essentially an artificial neural network (ANN) and a fuzzy logic system (FLS), in order to build an adaptive model capable of improving both the physical reliability and the computational efficiency of a KMC model fully parameterized on MD results.
| Original language | English |
|---|---|
| Title of host publication | Applied Artificial Intelligence |
| Subtitle of host publication | Proceedings of the 7th International FLINS Conference, FLINS 2006 |
| Editors | Pierre D'Hondt, Etienne E. Kerre, Da Ruan, Martine De Cock, Mike Nachtegael, Paolo F. Fantoni |
| Place of Publication | Singapore, Singapore |
| Publisher | World Scientific Publishing Co. Pte Ltd |
| Pages | 883-890 |
| Number of pages | 8 |
| Volume | 1 |
| ISBN (Electronic) | 9789814478472 |
| ISBN (Print) | 9789812566904 |
| DOIs | |
| State | Published - 2006 |
| Event | 2006 - 7th international FLINS conference on Fuzzy Logic and Intelligent technologies in Nuclear Science - Genova Duration: 29 Aug 2006 → 31 Aug 2006 Conference number: FLINS2006 |
Publication series
| Name | Applied Artificial Intelligence - Proceedings of the 7th International FLINS Conference, FLINS 2006 |
|---|
Conference
| Conference | 2006 - 7th international FLINS conference on Fuzzy Logic and Intelligent technologies in Nuclear Science |
|---|---|
| Country/Territory | Italy |
| City | Genova |
| Period | 2006-08-29 → 2006-08-31 |
ASJC Scopus subject areas
- Information Systems
- Computational Theory and Mathematics
- Nuclear and High Energy Physics
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